Literature DB >> 12855461

APDB: a novel measure for benchmarking sequence alignment methods without reference alignments.

Orla O'Sullivan1, Mark Zehnder, Des Higgins, Philipp Bucher, Aurelien Grosdidier, Cédric Notredame.   

Abstract

MOTIVATION: We describe APDB, a novel measure for evaluating the quality of a protein sequence alignment, given two or more PDB structures. This evaluation does not require a reference alignment or a structure superposition. APDB is designed to efficiently and objectively benchmark multiple sequence alignment methods.
RESULTS: Using existing collections of reference multiple sequence alignments and existing alignment methods, we show that APDB gives results that are consistent with those obtained using conventional evaluations. We also show that APDB is suitable for evaluating sequence alignments that are structurally equivalent. We conclude that APDB provides an alternative to more conventional methods used for benchmarking sequence alignment packages.

Mesh:

Year:  2003        PMID: 12855461     DOI: 10.1093/bioinformatics/btg1029

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  10 in total

1.  3DCoffee@igs: a web server for combining sequences and structures into a multiple sequence alignment.

Authors:  Olivier Poirot; Karsten Suhre; Chantal Abergel; Eamonn O'Toole; Cedric Notredame
Journal:  Nucleic Acids Res       Date:  2004-07-01       Impact factor: 16.971

2.  MUSCLE: multiple sequence alignment with high accuracy and high throughput.

Authors:  Robert C Edgar
Journal:  Nucleic Acids Res       Date:  2004-03-19       Impact factor: 16.971

3.  Improving the alignment quality of consistency based aligners with an evaluation function using synonymous protein words.

Authors:  Hsin-Nan Lin; Cédric Notredame; Jia-Ming Chang; Ting-Yi Sung; Wen-Lian Hsu
Journal:  PLoS One       Date:  2011-12-02       Impact factor: 3.240

4.  Automatic assessment of alignment quality.

Authors:  Timo Lassmann; Erik L L Sonnhammer
Journal:  Nucleic Acids Res       Date:  2005-12-16       Impact factor: 16.971

5.  A statistical score for assessing the quality of multiple sequence alignments.

Authors:  Virpi Ahola; Tero Aittokallio; Mauno Vihinen; Esa Uusipaikka
Journal:  BMC Bioinformatics       Date:  2006-11-03       Impact factor: 3.169

6.  MUMMALS: multiple sequence alignment improved by using hidden Markov models with local structural information.

Authors:  Jimin Pei; Nick V Grishin
Journal:  Nucleic Acids Res       Date:  2006-08-26       Impact factor: 16.971

Review 7.  IVisTMSA: Interactive Visual Tools for Multiple Sequence Alignments.

Authors:  Muhammad Tariq Pervez; Masroor Ellahi Babar; Asif Nadeem; Naeem Aslam; Nasir Naveed; Sarfraz Ahmad; Shah Muhammad; Salman Qadri; Muhammad Shahid; Tanveer Hussain; Maryam Javed
Journal:  Evol Bioinform Online       Date:  2015-03-12       Impact factor: 1.625

Review 8.  Upcoming challenges for multiple sequence alignment methods in the high-throughput era.

Authors:  Carsten Kemena; Cedric Notredame
Journal:  Bioinformatics       Date:  2009-07-30       Impact factor: 6.937

9.  Quality measures for protein alignment benchmarks.

Authors:  Robert C Edgar
Journal:  Nucleic Acids Res       Date:  2010-01-04       Impact factor: 16.971

Review 10.  Recent evolutions of multiple sequence alignment algorithms.

Authors:  Cédric Notredame
Journal:  PLoS Comput Biol       Date:  2007-08       Impact factor: 4.475

  10 in total

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